Unlocks after Module 8The AI Engineering Program

Module 9: Evals, Guardrails & AI Security

Measure whether an AI system is actually good, catch regressions before users do, and defend it against prompt injection and data leaks.

24guided hours
11lessons
9 of 13in the program

Lessons

11 lessons, in order. Each one unlocks when you finish the one before it.

  1. 9.1
    Why AI apps fail silently
  2. 9.2
    Error analysis on real traces
  3. 9.3
    Golden datasets and synthetic test data
  4. 9.4
    Code-based checks and assertions
  5. 9.5
    LLM-as-judge, calibrated against human labels
  6. 9.6
    Evals in CI: blocking a bad prompt change
  7. 9.7
    Tracing and observability with open-source tools
  8. 9.8
    OWASP Top 10 for LLM apps: prompt injection, data leakage, excessive agency
  9. 9.9
    Guardrails and personal-data redaction
  10. 9.10
    Red-teaming your own app
  11. 9.11
    Module project

Your first lesson is on us.

AI vs ML vs DL vs GenAI: deep notes, a hands-on lab and a quiz. No card. No catch.